The purpose of the proposed project is to model the dynamic behavior of a sick individual with regard to the use of medical care services and work absences in order to quantify the effects of individual differences and to evaluate the impact of different public policies. Using public use data from the 1987 National Medical Expenditure Survey, this research will explain the extent to which differences in income, socioeconomic background, and health insurance and sick leave coverage affect the duration of illness and the frequency of medical care use and absenteeism. Estimates of the importance of gender, race, income, education, and illness severity in predicting the probabilities of seeking treatment and of missing work will be obtained. the solution method involves solving the discrete stochastic dynamic programming problem with recursive substitution. The estimation procedure involves full-information maximization of a nonlinear likelihood function derived from the optimal decision rules and the assumed distributions of the state variables and the random unobservables in the model. Implementation of a dynamic stochastic model of optimal medical care utilization and work absenteeism and estimation of the relevant structural parameters of the theoretical model will allow for the evaluation of various new policies including extension of insurance coverage and mandatory leave provision.